In the field of automotive driver information display systems, a user (e.g. driver) is provided with large amounts of different information, for example ranging from vehicle/engine information provided by way of an instrument cluster, navigation information provided by way of a navigation system, media and entertainment (infotainment) related information provided by way of an infotainment system, etc. Conventionally, the various different types of information are provided by way of separate graphics processing units (GPUs) and multiple displays. In order to reduce costs, complexity, etc., there is a desire for the various information display systems to share a single GPU in near future automotive systems, whereby a single GPU is used to provide the various different types of information to the user via one or more displays.
An instrument cluster provides critical, time-sensitive information to a driver of a vehicle, such as the speed of the vehicle etc. Accordingly, the instrument cluster is a critical module and the timely display of information thereby is also critical. The instrument cluster therefore needs to have access to the GPU in a timely manner, and with a certain level of determinism. In order to be able to guarantee the number of frames per second required by the instrument cluster module when using a shared GPU, whilst optimising overall throughput of the GPU, one has to estimate the required run time duration of other modules accessing the shared GPU.
In future systems, it is contemplated that users may be able to download additional software applications (for example as part of an infotainment module functionality), complicating the task of estimating the required run time duration of non-instrument cluster modules accessing the shared GPU.